AsiaRiceYield4km: seasonal rice yield in Asia from 1995 to 2015
文献类型：期刊论文
| 作者 | Wu, Huaqing1; Zhang, Jing2; Zhang, Zhao1; Han, Jichong1; Cao, Juan1; Zhang, Liangliang1; Luo, Yuchuan1; Mei, Qinghang1; Xu, Jialu1; Tao, Fulu3,4 |
| 刊名 | EARTH SYSTEM SCIENCE DATA
 |
| 出版日期 | 2023-02-14 |
| 卷号 | 15期号:2页码:791-808 |
| DOI | 10.5194/essd-15-791-2023 |
| 文献子类 | Article |
| 英文摘要 | Rice is the most important staple food in Asia. However, high-spatiotemporal-resolution rice yield datasets are limited over this large region. The lack of such products greatly hinders studies that are aimed at accurately assessing the impacts of climate change and simulating agricultural production. Based on annual rice maps in Asia, we incorporated multisource predictors into three machine learning (ML) models to generate a high-spatial-resolution (4 km) seasonal rice yield dataset (AsiaRiceYield4km) for the 1995-2015 period. Predictors were divided into four categories that considered the most comprehensive rice growth conditions, and the optimal ML model was determined based on an inverse probability weighting method. The results showed that AsiaRiceYield4km achieves good accuracy for seasonal rice yield estimation (single rice: R-2=0.88, RMSE = 920 kg ha(-1); double rice: R-2=0.91, RMSE = 554 kg ha(-1); and triple rice: R-2=0.93, RMSE = 588 kg ha(-1)). Compared with single rice from the Spatial Production Allocation Model (SPAM), the R-2 of AsiaRiceYield4km was improved by 0.20, and the RMSE was reduced by 618 kg ha(-1) on average. In particular, constant environmental conditions, including longitude, latitude, elevation and soil properties, contributed the most (similar to 45 %) to rice yield estimation. For different rice growth periods, we found that the predictors of the reproductive period had greater impacts on rice yield prediction than those of the vegetative period and the whole growing period. AsiaRiceYield4km is a novel long-term gridded rice yield dataset that can fill the unavailability of high-spatial-resolution seasonal yield products across major rice production areas and promote more relevant studies on agricultural sustainability worldwide. |
| WOS关键词 | LEAF-AREA INDEX ; TIME-SERIES ; WINTER-WHEAT ; PREDICTION ; SATELLITE ; CLIMATE ; IMPACTS ; MODEL ; VALIDATION ; PRODUCTS |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences |
| WOS记录号 | WOS:000933301100001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200746]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 作者单位 | 1.Beijing Normal Univ, Key Lab Environm Change & Nat Disasters, Minist Educ, Beijing 100875, Peoples R China 2.Beijing Normal Univ, Sch Natl Safety & Emergency Management, Beijing 100875, Peoples R China 3.Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 5.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Huaqing,Zhang, Jing,Zhang, Zhao,et al. AsiaRiceYield4km: seasonal rice yield in Asia from 1995 to 2015[J]. EARTH SYSTEM SCIENCE DATA,2023,15(2):791-808. |
| APA | Wu, Huaqing.,Zhang, Jing.,Zhang, Zhao.,Han, Jichong.,Cao, Juan.,...&Tao, Fulu.(2023).AsiaRiceYield4km: seasonal rice yield in Asia from 1995 to 2015.EARTH SYSTEM SCIENCE DATA,15(2),791-808. |
| MLA | Wu, Huaqing,et al."AsiaRiceYield4km: seasonal rice yield in Asia from 1995 to 2015".EARTH SYSTEM SCIENCE DATA 15.2(2023):791-808. |
入库方式： OAI收割
来源：地理科学与资源研究所
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